I'm running an ANOVA model. I found my model does not meet constant variance assumption and corrected for that using a weighted ANOVA model. I don't think that changes anything..
After I run the weighted ANOVA model in SAS, I find one of my fixed effects is not significant with p-value = 0.3, but when I run LSMEANS on that same fixed effect, one of the levels shows statistical significance with p-value < .0001 compared to all the other levels.
What does that mean?
Edit: My data set is 1500 observations. It is unbalanced. I nested a variable. The variables in question are var1 and var2. Both are not significant in overall model. But LSMEANs says they are significant. Someone answered that to the response variable (score), these variables are not significant, but the means among each other are different?
proc glm data=weights2; weight wt; class var1 var2 var3 var4; model score = var1|var2|var4 @2 var1|var2|var3(var4) /solution; random var2 var1*var2 var2*var4 var2*var3(var4) var1*var2*var3(var4) /test; output out=myoutb r=res p=fitted; lsmeans var1*var2*var3(var4) /pdiff; lsmeans var3(var4) /pdiff; lsmeans var1 /pdiff; lsmeans var2 /pdiff; lsmeans var4 /pdiff; run;